and here is the code that produced it
reset f(x) = exp(-x/10.0)*sin(x) g(x) = exp(-x/10.0) h(x) = -exp(-x/10.0) set sample 30 set table 'test.dat' plot [0:20] f(x)+(rand(0)-0.5)*0.2 unset table set sample 100 set multiplot set palette model RGB functions 0.4+gray/1.667, 0.75+gray/4.0, 0.4+gray/1.667 set pm3d map set isosample 100,100 set yrange [-1:1] unset colorbox unset border unset xtics unset ytics set size 1.5,1.6 set origin -.25,-.3 splot y t '' set palette model RGB functions 0.9+gray/10.0, 0.5+gray/2.0, 0.5+gray/2.0 set size 1.208, 1.295 set origin -0.065,-0.125 splot [0:20] y t '' set size 1,1 set origin 0,0 set xtics set ytics set xlabel 'Time [s]' set ylabel 'Position [m]' set border 1+2+4+8 set key reverse box plot [0:20] f(x) w l lt 3 lw 2 t 'y=sin(x)*exp(-x/10) ', \ g(x) w l lt rgb "#008800" t '', h(x) w l lt rgb "#008800" t '', \ 'test.dat' u 1:2:($2-rand(0)*0.1-0.05):($2+rand(0)*0.1+0.05) w errorb pt 13 lt 1 t 'Data set 2 ' unset multiplot
Now, let us see what is happening here. The first couple of lines are there just to produce some data (in this case, a damped oscillation with some random noise). The interesting part begins with 'set multiplot': we define a palette, which will run between some shade of green and white. This will be our background for the whole image. It will have a gradient, because we plot the function 'y', so as we go towards the top, the colour becomes whiter and whiter. In order to cover the whole canvas, we have to play with the size a bit, but this should be more or less straightforward.
In the second plot, the only thing that really is different is the colour palette, which, this time, is from some shade of red to white. Again, you might have to set the size of the plot by hand, and this might also depend on the actual terminal that you are using.
In the last part, we set the labels and the border (if you cast a glance at the code, you'll notice that these were switched off at the beginning), and plot our functions and data. Since I wanted to show errorbars, I generated artificial errors with the rand(0) function. If you have a real data set that you want to plot, this should be much simpler. You can skip the first 7 lines, and just use the columns in your data file to show the errors.
There, you have it!